Interference signals are a major problem in the field of electronic communication signals and, in particular, with radar systems. Coming up with new and improved processes and solutions to sort out the unwanted interference signals from the desired signals is a continuing pursuit in the signal processing industry. Continuous Wave (CW) interference is one form of interference signal that is typically encountered in a number of Radio Frequency (RF) bands where radar systems operate. The presence of heavy CW interference in these RF bands is created in large part from commercial radio, TV, and cellular telephone transmissions.
In general, CW interference signals introduce a large average power presence into the radar system's passband as compared to the low average power of the desired radar pulses. This results in the desired pulses having a low signal-to-noise ratio (SNR) which makes detection difficult. With the need for a signal-to-noise ratio of 16-18 db typically required to detect and characterize pulses accurately, standard wideband video detectors are not able to successfully detect pulses on a consistent basis.
Therefore, in order for radar systems to maintain a high level of proper pulse detection, the CW interference signals must first be suppressed before further signal processing can take place. This suppression must be performed efficiently in order to keep the required computational resources to a minimum. Currently, CW interference signals are typically being dealt with through the use of a variety of known CW Interference Suppression (CWIS) techniques based in the frequency domain. Some typical applications are in the Intelligence, Surveillance and Reconnaissance (ISR) field where there is a need to detect various radar pulses in the midst of heavy CW interference. Generally, these CW interference suppression techniques operate to pre-process the data and allow pulse detection via matched detection matrices. However, such techniques are all generally very time-intensive requiring very large signal processing systems having special hardware for handling the heavy demand on computational resources.
In view of such, current CW interference suppression techniques are typically not adequate for all of today's CW interference suppression applications. Embedded systems are one such type of application where there is a growing demand for new and improved techniques for accomplishing CW interference suppression. Embedded systems are generally much smaller in hardware size having very limited computational resources as compared to the large signal processing systems that have typically employed CW interference suppression capabilities. Hence, current frequency domain based CW interference suppression techniques are just simply too compute intensive and too computational resource demanding for use in embedded systems.
Other CW interference suppression techniques have been employed utilizing digitized waveforms, Fast Fourier Transforms (FFTs) and Inverse Fast Fourier transforms (IFFTs) to operate on and process the signals. However, current CW interference techniques as such employed to digitally process the signals have exhibited problems with the Gibbs Phenomenon. The Gibbs Phenomenon occurs when processing signals that are not infinitely long. Generally, the Gibbs Phenomenon manifests itself in the form of false signal detections, ringing at the ends of pulses, and creation of new pulses which aren't actually present in the sensed signal by way of interpulse ringing and wrap-around effects. In short, the current CW interference suppression techniques known today in the industry employing digital processing and the use of FFTs, inherently carry a two-fold problem of distorted detected pulses and false detections. As a result, CW interference suppression techniques employed in the current systems of today simply live with these inherent problems and deal with them later through further post-processing the data.
Accordingly, there exists a long felt need for an improved CW interference suppression and pulse detection method and system that alleviates the inherent problems known in CW interference suppression systems currently being employed in the signal processing industry; and which is better suited for use in embedded system applications where computational resources are limited.